The Fuzzy PID Control of Resistance Furnace Temperature System Based on Genetic Algorithm

2013 ◽  
Vol 273 ◽  
pp. 678-682 ◽  
Author(s):  
Jing Yan Liu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Pid Control ◽  
Global Optimum ◽  
Fuzzy Pid ◽  
Matlab Simulation ◽  
Resistance Furnace ◽  
Fuzzy Pid Control ◽  
Furnace Temperature ◽  
Control Rules

The resistance furnace temperature system has low accuracy and big overshoots with fuzzy control. The fuzzy PID controller is used to optimize the resistance furnace temperature system, and the design scheme is developed. The fuzzy control and PID control are combined to control the system. If the system’s deviation is large the fuzzy control is adopted, else PID control is adopted. The genetic algorithm is adopted to train the controller’s membership functions, control rules and parameters. The global optimum of the controller’s parameters can be achieved. Matlab simulation results indicate that the resistance furnace temperature system with fuzzy PID control is more dynamic, robust, and highly precise.

Research on the Fuzzy PID Speed Control System of Permanent Magnet Linear Synchronous Motor Based on Genetic Algorithm

2014 ◽  
Vol 494-495 ◽  
pp. 1582-1586 ◽  
Author(s):  
Jun Liu ◽  
Qian Wei Xie
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Pid Control ◽  
Linear Time ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller ◽  
Stability Performance ◽  
Control Rules ◽  
Genetic Algorithm Method

Focusing on the non-linear, time-varying, strong coupling and external load disturbance existing in PMLSM, a fuzzy PID controller based on genetic algorithms is designed to control the speed of PMLSM by absorbing the advantages of PID control and fuzzy control, and the genetic algorithm method is used to optimize fuzzy control rules. A simulation experiment was made to compare the effects of traditional PID control and fuzzy PID based on genetic algorithm control by Matlab. The simulation results verify that fuzzy PID control based on genetic algorithm is superior to PID control in dynamic stability performance and speed tracking power.

Induction Heating Furnace Temperature Control Based on the Fuzzy PID

2012 ◽  
Vol 217-219 ◽  
pp. 2463-2466 ◽  
Author(s):  
Xue Gang Hou ◽  
Cheng Long Wang
Keyword(s):  
Fuzzy Control ◽  
Temperature Control ◽  
Induction Heating ◽  
Pid Control ◽  
Pid Controller ◽  
Heating Furnace ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Furnace Temperature ◽  
Run Up

Induction heating furnace temperature control is a complex nonlinear hysteretic inertial process, it's difficult to obtain an accurate mathematical model because the temperature and disturb from outside is complicated. The normal PID control algorithm is hard to satisfy the standards of control. The fuzzy PID controller provided in this article is a combination between fuzzy control and the traditional PID control. The Fuzzy control theory is used to setting the ratio, the integral and the differential coefficient of the PID control. In the run-up stage, rapidity is guaranteed, overstrike and the steady-state error is up to the mustard. An example indicates that fuzzy PID control is superior to the normal PID controller.

Research on Self-Tuning Fuzzy PID Control Strategy of Metallurgy Furnace Temperature

2012 ◽  
Vol 472-475 ◽  
pp. 3063-3066
Author(s):  
Rong Luo ◽  
Lun Wei Chen ◽  
Hong Bo Ren ◽  
Cheng Yu Liu
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Control Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Furnace Temperature ◽  
Advantages And Disadvantages ◽  
Self Tuning ◽  
Concrete Control

Aim at the effect of the control method in traditional metallurgy furnace temperature is not good, a self-tuning fuzzy PID control method combining fuzzy control with PID control was proposed in this paper based on the analysis of the advantages and disadvantages of the PID control and fuzzy control method, and a concrete control algorithm was put forward and simulation experiment was finished. The simulation results show that the effect of the controller is good, and the control of system is fast and smoothly according to it.

The Research on Self-Adaptive Fuzzy PID Controller

2013 ◽  
Vol 373-375 ◽  
pp. 1462-1465
Author(s):  
Bin Liu ◽  
Gang Yao ◽  
Xiao Bing Xiao ◽  
Xu Sheng Yin
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Pid Controller ◽  
Adaptive Fuzzy Control ◽  
Fuzzy Pid ◽  
Matlab Simulation ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Self Tuning ◽  
Self Adaptive

The parameters of the traditional proportional-integral-derivative (PID) controller are hard to automatically adjust when the controlled object changes, which controls ineffective for time-varying, nonlinear system. Combine the fuzzy control and PID control, and use self-adaptive fuzzy control to achieve self-tuning PID parameters online. Using matlab simulation system, the results show that the self-adaptive fuzzy PID control effects have been improved than the conventional PID control.

Development of a Novel Robotic Catheter Manipulating System with Fuzzy PID Control

2012 ◽  
Vol 2 (2) ◽  
pp. 58-77 ◽  
Author(s):  
Xu Ma ◽  
Shuxiang Guo ◽  
Nan Xiao ◽  
Jian Guo ◽  
Shunichi Yoshida ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Control Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fast Reactions ◽  
Control Rules ◽  
Remote Operations ◽  
Intense Radiation ◽  
Better Than

Manual operation of steerable catheter is inaccurate in minimally invasive surgery, requiring dexterity for efficient manipulation of the catheter, and it exposes the surgeons to intense radiation. The authors’ objectives are to develop a robotic catheter manipulating system that replaces the surgeons with high accuracy. Increasing demands for flexibility and fast reactions in a control method, fuzzy control (FC) can play an important role because the experience of experts can be combined in the fuzzy control rules to be implemented in the systems. They present a practical application of a fuzzy PID control to this developed system during the remote operations and compare with the traditional PID (Proportional-Integral-Derivative Controllers) control experimentally. The feasibility and effectiveness of the control method are demonstrated. The synchronous manipulation performance with the fuzzy PID control is much better than using the conventional PID control method during the remote operations.

Advanced design and tests of a new electrical control seeding system with genetic algorithm fuzzy control strategy

2021 ◽  
pp. 1-10
Author(s):  
Sheng Wang ◽  
Yanhong Sun ◽  
Chen Yang ◽  
Yongchang Yu
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Fuzzy Control ◽  
Electric Drive ◽  
Pid Control ◽  
Fuzzy Pid ◽  
Seeding Rate ◽  
Fuzzy Pid Control ◽  
Transmission Method ◽  
Better Than

In the existing soybean breeding and planting machinery, the power source of the metering device adopts the ground wheel transmission method mostly. However, this power transmission method is likely to cause slippage during the planting operation, which will cause problems such as the increase of the missed seeding index and the increase of the coefficient of plant spacing. It is not conducive for scientific researchers to carry out breeding operations. Aiming at this problem, an electronically controlled soybean seeding system is designed, and the power of the seed metering device is derived from the motor. In order to improve the control accuracy of the electronically controlled seeding system, the precise control of the soybean seeding rate is finally realized. The electric drive soybean seeding system adopts closed-loop control, the motor model of the electric drive seeding system is established, and the transfer function of the motor is obtained. PID control based on a genetic algorithm is adopted, and the corresponding parameters are substituted into the control system simulation model established in MATLAB/SIMULINK. Field verification tests have been carried out on the conventional fuzzy PID control system and the electric drive soybean planter of the fuzzy PID control system based on a genetic algorithm. The result showed that the average of the repeat-seeding parameter is 1.30% better than the average of conventional seeding system (1.40%), the average of the miss-seeding parameter is 1.08% better than the average of conventional seeding system (2.09%) and the average of row-spacing variation parameter is 2.79% better than the average of conventional seeding system (2.34%). In conclusion, the new seeding system is robust obviously. Field trial results show that seeding with Genetic Algorithm Fuzzy control is better.

Research and Application of Fuzzy Control in Boiler Combustion System Based on ACA

2012 ◽  
Vol 461 ◽  
pp. 642-646
Author(s):  
Chen Wu ◽  
Guo Huan Lou
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Ant Colony Algorithm ◽  
Control Method ◽  
Linear Time ◽  
Control Parameters ◽  
Combustion System ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Rules

In the complex control processes of the industrial boiler combustion system with non-linear, time-varying and multivariable, aim at the original control parameters fixed, slow response, delay regulation and other problems, this paper introduces a control method that combines ant colony algorithm with fuzzy PID control, improves the design of fuzzy control rules table and optimizes the PID control parameters. Simulation results show that this control scheme is superior to conventional PID control and fuzzy PID control.

Fuzzy PID Parameters Self-Tuning in the Application of the Furnace Temperature Control System

2015 ◽  
Vol 713-715 ◽  
pp. 849-853 ◽  
Author(s):  
Zheng Qiang Guan ◽  
Xiao Ming Luo ◽  
Le Peng Song
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Control Process ◽  
Temperature Control System ◽  
System Response ◽  
Fuzzy Pid ◽  
Matlab Simulation ◽  
Fuzzy Pid Control ◽  
Furnace Temperature ◽  
Self Tuning

According to the set temperature, the parameter self-tuning fuzzy PID control algorithm is used furnace temperature automatic control and fuzzy PID control process to make use of the MATLAB simulation. Simulation results show that compared with conventional PID control, the parameter self-tuning fuzzy PID control algorithm improves the system response, shorten the adjusting time, enhances the disruptive, demonstrate the superiority of the fuzzy PID.

Sign in / Sign up

Export Citation Format

Share Document